127 citations · 278 across the 14 of their papers we have counts for
6 papers · 1 filter
Learning Controllable Fair Representations
Jiaming Song, Pratyusha Kalluri, Aditya Grover +2
Learning data representations that are transferable and are fair with respect to certain protected attributes is crucial to reducing unfair decisions while preserving the utility o…
Bias and Generalization in Deep Generative Models: An Empirical Study
Shengjia Zhao, Hongyu Ren, Arianna Yuan +3
In high dimensional settings, density estimation algorithms rely crucially on their inductive bias. Despite recent empirical success, the inductive bias of deep generative models i…
Multi-Agent Generative Adversarial Imitation Learning
Jiaming Song, Hongyu Ren, Dorsa Sadigh +1
Imitation learning algorithms can be used to learn a policy from expert demonstrations without access to a reward signal. However, most existing approaches are not applicable in mu…
gSMat: A Scalable Sparse Matrix-based Join for SPARQL Query Processing
Xiaowang Zhang, Mingyue Zhang, Peng Peng +3
Resource Description Framework (RDF) has been widely used to represent information on the web, while SPARQL is a standard query language to manipulate RDF data. Given a SPARQL quer…
The Information Autoencoding Family: A Lagrangian Perspective on Latent Variable Generative Models
Shengjia Zhao, Jiaming Song, Stefano Ermon
A large number of objectives have been proposed to train latent variable generative models. We show that many of them are Lagrangian dual functions of the same primal optimization…
An Empirical Analysis of Proximal Policy Optimization with Kronecker-factored Natural Gradients
Jiaming Song, Yuhuai Wu
In this technical report, we consider an approach that combines the PPO objective and K-FAC natural gradient optimization, for which we call PPOKFAC. We perform a range of empirica…